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I have a data set with N/A appearing but the N/A means 0 so it isn't a missing value as such. Specifically, where there is no garage the data is N/A. I've followed the usual path to change to numeric, but it isn't working for me. I'm new to r so I have limited knowledge, but it's driving me nuts. How should I deal with this issue?

Tam Brook
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  • Have you tried `mydata[is.na(mydata)] <- 0` – Daniel O Apr 06 '21 at 01:23
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    Please see my answer to see if this works or if you have any questions. In the future, it is better to include a reproducible example. It will make others easier to answer your question. – www Apr 06 '21 at 01:26
  • One of this link should work for you https://stackoverflow.com/questions/8161836/how-do-i-replace-na-values-with-zeros-in-an-r-dataframe. If you have string "NA" use `mydata[mydata == 'NA'] <- 0` like in this link https://stackoverflow.com/questions/11036989/replace-all-0-values-to-na – Ronak Shah Apr 06 '21 at 01:35

2 Answers2

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Here is one idea. We can use ifelse to replace a target value to 0.

# Create an example data frame
dat <- data.frame(a = c("1", "5", "3", "N/A"),
                  b = c("a", "b", "c", "d"))

# Replace N/A with 0 in column a
dat$a <- ifelse(dat$a %in% "N/A", "0", dat$a)
# Convert column a to numeric
dat$a <- as.numeric(dat$a)

# See the results
dat
#   a b
# 1 1 a
# 2 5 b
# 3 3 c
# 4 0 d
www
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I edited my response to this question:

library(dplyr)
library(readr)
library(stringr)

df <- tibble(x = c("1", "2", "N/A"), y = c("4", "N/A", "5"))

df %>%
  mutate(across(x:y, ~ str_replace(.x, "N/A", "0")), 
         across(x:y, ~ parse_double(.x))) 

# A tibble: 3 x 2
      x     y
  <dbl> <dbl>
1     1     4
2     2     0
3     0     5
Anoushiravan R
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